Uncovering the algorithmic foundations of language learning and processing

Abstract: Human language is extraordinarily complex. Nevertheless, we readily acquire language as children, when we are most cognitively limited, and we comprehend language as adults with striking efficiency. My research seeks to understand the mental algorithms that allow us to accomplish this feat, with particular focus on how memory and prediction mechanisms are recruited to overcome the bottlenecks of real-time language processing. In this talk, I will review results from three of my lines of inquiry into this question. First, using diverse naturalistic reading datasets, I will show evidence that prediction is a central concern of the human language processing system. Second, using fMRI measures of naturalistic story listening, I will show evidence that memory and prediction processes are dissociable in the brain’s response to language, that syntactic structure building plays a major role in ordinary language comprehension, and that the neural resources that are responsible for structure building are largely specialized for language. Third, I will show evidence from computational modeling that memory and prediction pressures independently encourage discovery of phonological regularities from natural speech. Together, these results support an intricate coordination of memory and prediction abilities for language learning and comprehension. I will conclude by outlining planned directions for my future lab, integrating neuroimaging, behavioral methods, natural language processing, and computational modeling to study language learning and processing.

Bio: Cory is a post-doc at MIT and their work uses computational and experimental methods to study language and the mind, particularly (1) the cognitive processes that allow us to understand the things we hear and read so quickly, (2) the learning signals that we leverage as children to acquire language from the environment, and (3) the role played by real-time information processing constraints in shaping language learning and comprehension.